Abstract
This study extends the generalized true random-effects model to account for spatial dependence in persistent and transient inefficiency. For this purpose, a model with spatially autocorrelated persistent and transient inefficiency components is specified. Additionally, spatial dependence is also modeled in the noise component to account for uncontrolled spatial correlations. The proposed model is applied to a panel dataset of Wisconsin dairy farms observed between 2009 and 2017 and estimated using Bayesian techniques. Apart from the traditional output-input quantities, the utilized dataset also contains information on the exact location of farms based on their latitude and longitude coordinates as well as on environmental factors. The empirical findings suggest low levels of both persistent and transient inefficiency for farms. Additionally, all components exhibit spatial dependence with its magnitude being more than double for persistent inefficiency.
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